






"""simple docstring"""


import pickle
import shutil
import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


__SCREAMING_SNAKE_CASE   =   get_tests_dir('fixtures/test_sentencepiece.model')




@require_sentencepiece
@require_tokenizers
class 						__UpperCamelCase     (     UpperCamelCase   ,     unittest.TestCase						):
					lowercase_    :				List[Any]      =  XGLMTokenizer
					lowercase_    :				Dict      =  XGLMTokenizerFast
					lowercase_    :				Any      =  True
					lowercase_    :				Optional[int]      =  True
					def        UpperCAmelCase__ (							self							:	List[Any]   )	->       Optional[Any]:
											super().setUp()

											# We have a SentencePiece fixture for testing
											lowerCAmelCase   :Union[str, Any]						=			XGLMTokenizer(UpperCAmelCase     , keep_accents=UpperCAmelCase   )
											tokenizer.save_pretrained(self.tmpdirname   )
					def        UpperCAmelCase__ (							self							:	str   )	->       Dict:
											lowerCAmelCase   :List[str]						=			'<pad>'
											lowerCAmelCase   :Optional[Any]						=			1

											self.assertEqual(self.get_tokenizer()._convert_token_to_id(UpperCAmelCase   )     , UpperCAmelCase   )
											self.assertEqual(self.get_tokenizer()._convert_id_to_token(UpperCAmelCase   )     , UpperCAmelCase   )
					def        UpperCAmelCase__ (							self							:	int   )	->       Tuple:
											lowerCAmelCase   :List[str]						=			list(self.get_tokenizer().get_vocab().keys()   )

											self.assertEqual(vocab_keys[0]     , '<s>'   )
											self.assertEqual(vocab_keys[1]     , '<pad>'   )
											self.assertEqual(len(UpperCAmelCase   )     , 1008   )
					def        UpperCAmelCase__ (							self							:	List[str]   )	->       Tuple:
											self.assertEqual(self.get_tokenizer().vocab_size     , 1008   )
					def        UpperCAmelCase__ (							self							:	Any   )	->       Tuple:
											lowerCAmelCase   :Union[str, Any]						=			XGLMTokenizer(UpperCAmelCase     , keep_accents=UpperCAmelCase   )

											lowerCAmelCase   :Any						=			tokenizer.tokenize('This is a test'   )
											self.assertListEqual(UpperCAmelCase     , ['▁This', '▁is', '▁a', '▁t', 'est']   )

											self.assertListEqual(
											    tokenizer.convert_tokens_to_ids(UpperCAmelCase   )     , [value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]     , )

											lowerCAmelCase   :Any						=			tokenizer.tokenize('I was born in 92000, and this is falsé.'   )
											self.assertListEqual(
											    UpperCAmelCase     , [
											        SPIECE_UNDERLINE + 'I',
											        SPIECE_UNDERLINE + 'was',
											        SPIECE_UNDERLINE + 'b',
											        'or',
											        'n',
											        SPIECE_UNDERLINE + 'in',
											        SPIECE_UNDERLINE + '',
											        '9',
											        '2',
											        '0',
											        '0',
											        '0',
											        ',',
											        SPIECE_UNDERLINE + 'and',
											        SPIECE_UNDERLINE + 'this',
											        SPIECE_UNDERLINE + 'is',
											        SPIECE_UNDERLINE + 'f',
											        'al',
											        's',
											        'é',
											        '.',
											    ]     , )
											lowerCAmelCase   :int						=			tokenizer.convert_tokens_to_ids(UpperCAmelCase   )
											self.assertListEqual(
											    UpperCAmelCase     , [
											        value + tokenizer.fairseq_offset
											        for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
											    ]     , )

											lowerCAmelCase   :Tuple						=			tokenizer.convert_ids_to_tokens(UpperCAmelCase   )
											self.assertListEqual(
											    UpperCAmelCase     , [
											        SPIECE_UNDERLINE + 'I',
											        SPIECE_UNDERLINE + 'was',
											        SPIECE_UNDERLINE + 'b',
											        'or',
											        'n',
											        SPIECE_UNDERLINE + 'in',
											        SPIECE_UNDERLINE + '',
											        '<unk>',
											        '2',
											        '0',
											        '0',
											        '0',
											        ',',
											        SPIECE_UNDERLINE + 'and',
											        SPIECE_UNDERLINE + 'this',
											        SPIECE_UNDERLINE + 'is',
											        SPIECE_UNDERLINE + 'f',
											        'al',
											        's',
											        '<unk>',
											        '.',
											    ]     , )
					@cached_property
					def        UpperCAmelCase__ (							self							:	Optional[int]   )	->       Union[str, Any]:
											return XGLMTokenizer.from_pretrained('facebook/xglm-564M'   )
					def        UpperCAmelCase__ (							self							:	Dict   )	->       Optional[int]:
											with tempfile.NamedTemporaryFile() as f:
																	shutil.copyfile(UpperCAmelCase     , f.name   )
																	lowerCAmelCase   :Tuple						=			XGLMTokenizer(f.name     , keep_accents=UpperCAmelCase   )
																	lowerCAmelCase   :Union[str, Any]						=			pickle.dumps(UpperCAmelCase   )
											pickle.loads(UpperCAmelCase   )
					def        UpperCAmelCase__ (							self							:	int   )	->       List[Any]:
											if not self.test_rust_tokenizer:
																	return

											lowerCAmelCase   :str						=			self.get_tokenizer()
											lowerCAmelCase   :Dict						=			self.get_rust_tokenizer()

											lowerCAmelCase   :Optional[Any]						=			'I was born in 92000, and this is falsé.'

											lowerCAmelCase   :str						=			tokenizer.tokenize(UpperCAmelCase   )
											lowerCAmelCase   :Optional[int]						=			rust_tokenizer.tokenize(UpperCAmelCase   )
											self.assertListEqual(UpperCAmelCase     , UpperCAmelCase   )

											lowerCAmelCase   :str						=			tokenizer.encode(UpperCAmelCase     , add_special_tokens=UpperCAmelCase   )
											lowerCAmelCase   :Optional[int]						=			rust_tokenizer.encode(UpperCAmelCase     , add_special_tokens=UpperCAmelCase   )
											self.assertListEqual(UpperCAmelCase     , UpperCAmelCase   )

											lowerCAmelCase   :Optional[Any]						=			self.get_rust_tokenizer()
											lowerCAmelCase   :Union[str, Any]						=			tokenizer.encode(UpperCAmelCase   )
											lowerCAmelCase   :Union[str, Any]						=			rust_tokenizer.encode(UpperCAmelCase   )
											self.assertListEqual(UpperCAmelCase     , UpperCAmelCase   )
					@slow
					def        UpperCAmelCase__ (							self							:	Optional[Any]   )	->       Tuple:
											lowerCAmelCase   :Union[str, Any]						=			'Hello World!'
											lowerCAmelCase   :Tuple						=			[2, 3_1227, 4447, 35]

											self.assertListEqual(UpperCAmelCase     , self.big_tokenizer.encode(UpperCAmelCase   )   )
					@slow
					def        UpperCAmelCase__ (							self							:	Optional[int]   )	->       int:
											lowerCAmelCase   :Any						=			(
											    'This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) " [ ] ! : - . Also we will'
											    ' add words that should not exsist and be tokenized to unk, such as saoneuhaoesuth'
											)
											# fmt: off
											lowerCAmelCase   :Optional[Any]						=			[2, 1018, 67, 11, 1988, 2617, 5631, 278, 11, 3407, 48, 7_1630, 2_8085, 4, 3234, 157, 13, 6, 5, 6, 4, 3526, 768, 15, 659, 57, 298, 3983, 864, 129, 21, 6, 5, 1_3675, 377, 652, 7580, 1_0341, 155, 2817, 422, 1666, 7, 1674, 53, 113, 20_2277, 1_7892, 33, 60, 87, 4, 3234, 157, 61, 2667, 5_2376, 19, 88, 23, 735]
											# fmt: on

											self.assertListEqual(UpperCAmelCase     , self.big_tokenizer.encode(UpperCAmelCase   )   )
					@slow
					def        UpperCAmelCase__ (							self							:	List[Any]   )	->       Optional[Any]:
											# fmt: off
											lowerCAmelCase   :Optional[int]						=			{
											    'input_ids': [[2, 10_8825, 1163, 15, 8_8010, 473, 1_5898, 157, 1_3672, 1857, 312, 8, 23_8021, 1163, 53, 1_3672, 1857, 312, 8, 5_3283, 18_2396, 8, 1_8566, 16, 3_6733, 4101, 8, 230, 24_4017, 12_2553, 7, 15, 13_2597, 4, 293, 1_2511, 7610, 4, 3414, 13_2597, 9, 4, 3_2361, 362, 4, 734, 2_8512, 3_2569, 18, 4, 3_2361, 2_6096, 1_4982, 73, 1_8715, 2_1433, 23_5261, 15, 492, 1_2427, 16, 53, 1_8715, 2_1433, 6_5454, 15, 2_3659, 563, 16, 278, 597, 2843, 595, 7931, 18_2396, 6_4186, 22, 886, 595, 13_2981, 53, 2_5540, 3449, 4_3982, 3_9901, 5951, 878, 330, 4, 2_7694, 8_0269, 312, 53, 6517, 1_1780, 611, 2_0408, 5], [2, 6, 13_2597, 67, 4_2897, 33, 592, 8, 16_3729, 2_5540, 361, 13_6997, 10_9514, 17_3230, 7, 501, 60, 10_2913, 196, 5631, 235, 6_3243, 473, 6, 23_1757, 74, 5277, 7905, 53, 3095, 3_7317, 22, 454, 18_3874, 5], [2, 268, 3_1298, 4_6530, 6, 13_2935, 4_3831, 7, 597, 32, 24, 3688, 9865, 5]],
											    'attention_mask': [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
											}  # noqa: E501
											# fmt: on

											self.tokenizer_integration_test_util(
											    expected_encoding=UpperCAmelCase     , model_name='facebook/xglm-564M'     , padding=UpperCAmelCase     , )







"""simple docstring"""


import unittest

import numpy as np

from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
    is_onnx_available,
    load_image,
    load_numpy,
    nightly,
    require_onnxruntime,
    require_torch_gpu,
)


if is_onnx_available():
		import onnxruntime as ort




@nightly
@require_onnxruntime
@require_torch_gpu
class 						__UpperCamelCase     (     unittest.TestCase						):
					@property
					def        UpperCAmelCase__ (							self							:	Union[str, Any]   )	->       Dict:
											return (
											    "CUDAExecutionProvider",
											    {
											        "gpu_mem_limit": "15000000000",  # 15GB
											        "arena_extend_strategy": "kSameAsRequested",
											    },
											)
					@property
					def        UpperCAmelCase__ (							self							:	int   )	->       Optional[Any]:
											lowerCAmelCase   :Any						=			ort.SessionOptions()
											lowerCAmelCase   :Dict						=			False
											return options
					def        UpperCAmelCase__ (							self							:	Tuple   )	->       str:
											lowerCAmelCase   :Union[str, Any]						=			load_image(
											    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
											    '/in_paint/overture-creations-5sI6fQgYIuo.png'   )
											lowerCAmelCase   :str						=			load_image(
											    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
											    '/in_paint/overture-creations-5sI6fQgYIuo_mask.png'   )
											lowerCAmelCase   :List[Any]						=			load_numpy(
											    'https://huggingface.co/datasets/hf-internal-testing/diffusers-images/resolve/main'
											    '/in_paint/red_cat_sitting_on_a_park_bench_onnx.npy'   )

											# using the PNDM scheduler by default
											lowerCAmelCase   :Tuple						=			OnnxStableDiffusionInpaintPipelineLegacy.from_pretrained(
											    'CompVis/stable-diffusion-v1-4'     , revision='onnx'     , safety_checker=UpperCAmelCase     , feature_extractor=UpperCAmelCase     , provider=self.gpu_provider     , sess_options=self.gpu_options     , )
											pipe.set_progress_bar_config(disable=UpperCAmelCase   )

											lowerCAmelCase   :Optional[Any]						=			'A red cat sitting on a park bench'

											lowerCAmelCase   :Optional[Any]						=			np.random.RandomState(0   )
											lowerCAmelCase   :Union[str, Any]						=			pipe(
											    prompt=UpperCAmelCase     , image=UpperCAmelCase     , mask_image=UpperCAmelCase     , strength=0.7_5     , guidance_scale=7.5     , num_inference_steps=15     , generator=UpperCAmelCase     , output_type='np'     , )

											lowerCAmelCase   :Optional[int]						=			output.images[0]

											assert image.shape == (512, 512, 3)
											assert np.abs(expected_image - image   ).max() < 1e-2